Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
11,177
datasets available to search
ShareScore release 0.9.0
Dataset results
11,177 results for “identify”
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Zabdi Lopez, <a href="https://orcid.org/0000-0003-0449-7352">https://orcid.org/0000-0003-0449-7352</a>. Claims were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Anders Endrestøl, <a href="https://orcid.org/0000-0001-5869-6598">https://orcid.org/0000-0001-5869-6598</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Øivind Gammelmo, <a href="https://orcid.org/0000-0002-6026-9023">https://orcid.org/0000-0002-6026-9023</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Joaquim Santos, <a href="https://orcid.org/0000-0002-2160-4968">https://orcid.org/0000-0002-2160-4968</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Yiselle Cano-Cobos, <a href="https://orcid.org/0000-0001-6852-4239">https://orcid.org/0000-0001-6852-4239</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Santiago Andrés-Sánchez, <a href="https://orcid.org/0000-0002-8088-1607">https://orcid.org/0000-0002-8088-1607</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Michael D. Pirie, <a href="https://orcid.org/0000-0003-0403-4470">https://orcid.org/0000-0003-0403-4470</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Data for: Using distribution models to identify range shifts of four Acroneuria Pictet, 1841 (Plecoptera: Perlidae) species in the Midwest USA
<p><span></span></p> <p>Regional faunal assessments of stoneflies in the United States Midwest (herein defined as Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio, and Wisconsin) indicate increasing imperilment resulting from human disturbance and climate change. Large-bodied Perlid stoneflies with multivoltine life cycles are among the most at risk for regional extirpation, with losses reported in several midwestern states. Species distribution modeling was undertaken to describe distribution shifts for four widespread riverine species: <em>Acroneuria</em> <em>abnormis</em> (Newman, 1838), <em>A. frisoni </em>Stark & Brown, 1991, <em>A. internata </em>(Walker, 1852) and <em>A. lycorias</em> (Newman, 1839). The distribution modeling algorithm MaxEnt was selected to predict both the historical (i.e., pre-1960) and contemporaneous distributions for each species using separate occurrence datasets. These models permit the identification of suitable habitat loss through range contractions associated with human disturbance. Predictions of suitable habitat losses were recorded for multiple species but were greatest for<em> A. abnormis</em> and <em>A</em>. <em>internata</em>. These models serve to guide future collection efforts and to further describe patterns of regional biodiversity loss. The data presented within this dataset contain the occurrence data used for modeling with distinction between temporal periods modeled.</p>
Results of linear ocean model experiment for: Dual wave energy sources for the Atlantic Niño events identified by wave energy flux in case studies
<p>These are sensitivity experiments designed by manipulating the wind forcing that drives the linear ocean model to investigate the difference in equatorial waves in 1999, 2019, and 2021. </p>
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Mac Alford, <a href="https://orcid.org/0000-0002-3448-9735">https://orcid.org/0000-0002-3448-9735</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Sangmi Lee, <a href="https://orcid.org/0000-0002-9636-8242">https://orcid.org/0000-0002-9636-8242</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Piper Preuss, <a href="https://orcid.org/0009-0004-4438-6176">https://orcid.org/0009-0004-4438-6176</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Piper Preuss, <a href="https://orcid.org/0009-0004-4438-6176">https://orcid.org/0009-0004-4438-6176</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
(SNP Array) Single-Cell Multi-Omics Identifies Chronic Inflammation as a Driver of TP53 mutant Leukaemic Evolution
<p>Single nucleotide polymorphism (SNP) array data files related our publication titled "Single-Cell Multi-Omics Identifies Chronic Inflammation as a Driver of <em>TP53 </em>mutant Leukaemic Evolution".</p>
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Rick Overson, <a href="https://orcid.org/0000-0003-3728-6260">https://orcid.org/0000-0003-3728-6260</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Paradata datasets for: Identifying a Set of Key Paradata Indicators in Web Surveys
<p>Paradata datasets for Identifying a Set of Key Paradata Indicators in Web Surveys Based on the Relationship with Response Quality, Respondent Characteristics and Substantive Variables</p>
Data from: Identifying links between the biodiversity impacts and monetary costs of alien birds
<p>This dataset accompanies a published paper (Evans et al. 2023) which aims to identify links between the biodiversity impacts and monetary costs of alien bird species. In this paper we used mixed-effects models to test: (1) whether alien bird species with severe biodiversity impacts also had high monetary costs; (2) whether specific types of biodiversity impacts were associated with high monetary costs; and (3) whether certain factors caused alien bird species to have both severe biodiversity impacts and high monetary costs. This dataset includes all data used for the analysis, including biodiversity impact scores and monetary costs for each alien bird species, and the variables tested for their influence on these biodiversity impacts and costs. Please refer to Evans et al. (2023) for details on the methods used. The abstract to the published paper follows.</p> <ol> <li>Alien species can be damaging to native biodiversity, human well-being and the economy. Identifying the complete range of impacts they cause, and the ways that these impacts are connected, may inform the prioritisation of management actions to mitigate impacts.</li> <li>Using datasets on the biodiversity impacts and monetary costs (damage and management costs) of alien birds, we aimed to establish whether species with the most severe biodiversity impacts also had the highest costs; whether types of biodiversity impact were associated with high costs; and whether specific factors associated with alien species are linked to both damaging biodiversity impacts and high costs.</li> <li>We identified a positive relationship between a specific type of biodiversity impact (predation) and costs, possibly because predation by alien birds can be severely damaging to native species and therefore attracts management actions. However, predation impacts are likely to occur more frequently and to be easier to identify than some other impact mechanisms such as hybridisation and transmission of diseases, and they are therefore likely to be more frequently managed, and hence to have costs.</li> <li>We identified a specific species characteristic (generalism) to be associated with severe biodiversity impacts and high costs, probably because generalist species have greater opportunity to cause impacts, whether they be on biodiversity or the economy, or both. We also found widely distributed alien birds to be associated with high costs, probably also because these species have greater opportunity to cause impacts.</li> <li>Management interventions that prevent the introduction of both predatory and generalist alien bird species, or that reduce their geographic distribution at early stages of invasions, may have significant biodiversity and economic benefits.</li> </ol>
Data to D3.3 - Institutional arrangements of water supply, distribution and uses within and across case studies -identifying the barriers and drivers in place
<p>The transition towards a water circular economy (WCE) in the sense of water reuse may generate new water loops with additional challenges to water governance such as new and different types or qualities of water, new associated risks, new responsibilities,and new sets of actors involved. These challenges demand for clear-defined responsibilities, well-engaging of the various stakeholders, strong cooperation, and coordination among actors to prevent risks. Institutional arrangements, build the formal, and informal, design schemes to ensure adequate procedures and standards to better catalyse such transition. This deliverable analyses the institutional arrangements associated to the water management on the demosites, to assess their preparedness for the implementation of the new water loops as those foreseen with use of Project Ô new technologies. Using the Institutional Analysis and Development Framework, the analysis showed that the more water uses and users a new water loop involves the more critical the institutional arrangements become. Nevertheless, the institutional arrangements of the demosites do not always configure severe barriers. This is the case of Omis (Croatia) where the water reuse loop is located inside a textile company, and Eilat (Israel) where the water reuse loop is located inside amariculture centre. On the contrary, on Almendralejo (Spain) and Lecce (Italy), there are different players involved in the management ofthe water loop,andinstitutional arrangements appear more critical. Among the different institutional design principles, the clearly defined boundaries of responsibilities among stakeholders, the congruence between appropriation and provision rules and local conditions, raise more concerns on the case studies and call for the attention of future research on water circular economy. Fairly share of cost, benefits, and risks, dedicated graduated sanctions, conflict prevention and resolution mechanisms also deserve particular attention given the limited awareness of stakeholders of their features and influence for a successful implementation of demosites. Trust building, stakeholder empowerment and investment on transparency mechanisms related to water monitoring and sharing of communities and environmental benefits and costs of water reuse may be powerful approaches to implement water circular economy.</p>
Metabolites identified by UPLC-MS/MS method
<p>Metabolites identified by UPLC-MS/MS method including transition, expected retention time and potential overlaps</p>
Supplementary Material to "Identifying major research themes in sport sciences" (Dataset)
<p>The Excel file is organized into the following sheets:</p> <ul> <li><strong>SM_Sheet1</strong> - global bibliometric indicators in the sport sciences</li> <li><strong>SM_Sheet2</strong> - main indicators at country for two different period</li> <li><strong>SM_Sheet3</strong> - list of 4159 research topics for world science research</li> <li><strong>SM_Sheet4</strong> - a detailed description of main research topics in sport sciences</li> <li><strong>SM_Sheet5</strong> - the number of journals included in the Journal Citation Reports (JCR) in the sport science category and the topic distribution according to the Gini Index are as follows</li> </ul>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.